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Vallejo-Mancero B, Faci-Lázaro S, Zapata M, Soriano J, Madrenas J. Real-time hardware emulation of neural cultures: A comparative study of in vitro, in silico and in duris silico models. Neural Netw 2024; 179:106593. [PMID: 39142177 DOI: 10.1016/j.neunet.2024.106593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 06/20/2024] [Accepted: 07/31/2024] [Indexed: 08/16/2024]
Abstract
Biological neural networks are well known for their capacity to process information with extremely low power consumption. Fields such as Artificial Intelligence, with high computational costs, are seeking for alternatives inspired in biological systems. An inspiring alternative is to implement hardware architectures that replicate the behavior of biological neurons but with the flexibility in programming capabilities of an electronic device, all combined with a relatively low operational cost. To advance in this quest, here we analyze the capacity of the HEENS hardware architecture to operate in a similar manner as an in vitro neuronal network grown in the laboratory. For that, we considered data of spontaneous activity in living neuronal cultures of about 400 neurons and compared their collective dynamics and functional behavior with those obtained from direct numerical simulations (in silico) and hardware implementations (in duris silico). The results show that HEENS is capable to mimic both the in vitro and in silico systems with high efficient-cost ratio, and on different network topological designs. Our work shows that compact low-cost hardware implementations are feasible, opening new avenues for future, highly efficient neuromorphic devices and advanced human-machine interfacing.
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Affiliation(s)
- Bernardo Vallejo-Mancero
- Department of Electronic Engineering, Universitat Politecnica de Catalunya, Jordi Girona, 1-3, edif. C4, Barcelona, 08034, Catalunya, Spain.
| | - Sergio Faci-Lázaro
- Department of Condensed Matter Physics, University of Zaragoza, C. de Pedro Cerbuna, 12, Zaragoza, 50009, Spain; GOTHAM Lab, Institute of Biocomputation and Physics of Complex Systems, University of Zaragoza, C. de Pedro Cerbuna, 12, Zaragoza, 50009, Spain
| | - Mireya Zapata
- Department of Electronic Engineering, Universitat Politecnica de Catalunya, Jordi Girona, 1-3, edif. C4, Barcelona, 08034, Catalunya, Spain; Centro de Investigación en Mecatrónica y Sistemas Interactivos - MIST, Universidad Indoamérica, Machala y Sabanilla, Quito, 170103, Ecuador
| | - Jordi Soriano
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martíi Franquès 1, Barcelona, 08028, Spain; Universitat de Barcelona Institute of Complex Systems (UBICS), Gran Via Corts Catalanes 585, Barcelona, 08007, Spain
| | - Jordi Madrenas
- Department of Electronic Engineering, Universitat Politecnica de Catalunya, Jordi Girona, 1-3, edif. C4, Barcelona, 08034, Catalunya, Spain
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O'Neill KM, Anderson ED, Mukherjee S, Gandu S, McEwan SA, Omelchenko A, Rodriguez AR, Losert W, Meaney DF, Babadi B, Firestein BL. Time-dependent homeostatic mechanisms underlie brain-derived neurotrophic factor action on neural circuitry. Commun Biol 2023; 6:1278. [PMID: 38110605 PMCID: PMC10728104 DOI: 10.1038/s42003-023-05638-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 11/27/2023] [Indexed: 12/20/2023] Open
Abstract
Plasticity and homeostatic mechanisms allow neural networks to maintain proper function while responding to physiological challenges. Despite previous work investigating morphological and synaptic effects of brain-derived neurotrophic factor (BDNF), the most prevalent growth factor in the central nervous system, how exposure to BDNF manifests at the network level remains unknown. Here we report that BDNF treatment affects rodent hippocampal network dynamics during development and recovery from glutamate-induced excitotoxicity in culture. Importantly, these effects are not obvious when traditional activity metrics are used, so we delve more deeply into network organization, functional analyses, and in silico simulations. We demonstrate that BDNF partially restores homeostasis by promoting recovery of weak and medium connections after injury. Imaging and computational analyses suggest these effects are caused by changes to inhibitory neurons and connections. From our in silico simulations, we find that BDNF remodels the network by indirectly strengthening weak excitatory synapses after injury. Ultimately, our findings may explain the difficulties encountered in preclinical and clinical trials with BDNF and also offer information for future trials to consider.
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Affiliation(s)
- Kate M O'Neill
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ, USA
- Biomedical Engineering Graduate Program, Rutgers University, Piscataway, NJ, USA
- Institute for Physical Science & Technology, University of Maryland, College Park, MD, USA
| | - Erin D Anderson
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Shoutik Mukherjee
- Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA
| | - Srinivasa Gandu
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ, USA
- Cell and Developmental Biology Graduate Program, Rutgers University, Piscataway, NJ, USA
| | - Sara A McEwan
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ, USA
- Neuroscience Graduate Program, Rutgers University, Piscataway, NJ, USA
| | - Anton Omelchenko
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ, USA
- Neuroscience Graduate Program, Rutgers University, Piscataway, NJ, USA
| | - Ana R Rodriguez
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ, USA
- Biomedical Engineering Graduate Program, Rutgers University, Piscataway, NJ, USA
| | - Wolfgang Losert
- Department of Physics, University of Maryland, College Park, MD, USA
- Institute for Physical Science & Technology, University of Maryland, College Park, MD, USA
| | - David F Meaney
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Behtash Babadi
- Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA
| | - Bonnie L Firestein
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ, USA.
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Neuronal Cultures: Exploring Biophysics, Complex Systems, and Medicine in a Dish. BIOPHYSICA 2023. [DOI: 10.3390/biophysica3010012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Neuronal cultures are one of the most important experimental models in modern interdisciplinary neuroscience, allowing to investigate in a control environment the emergence of complex behavior from an ensemble of interconnected neurons. Here, I review the research that we have conducted at the neurophysics laboratory at the University of Barcelona over the last 15 years, describing first the neuronal cultures that we prepare and the associated tools to acquire and analyze data, to next delve into the different research projects in which we actively participated to progress in the understanding of open questions, extend neuroscience research on new paradigms, and advance the treatment of neurological disorders. I finish the review by discussing the drawbacks and limitations of neuronal cultures, particularly in the context of brain-like models and biomedicine.
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Montalà-Flaquer M, López-León CF, Tornero D, Houben AM, Fardet T, Monceau P, Bottani S, Soriano J. Rich dynamics and functional organization on topographically designed neuronal networks in vitro. iScience 2022; 25:105680. [PMID: 36567712 PMCID: PMC9768383 DOI: 10.1016/j.isci.2022.105680] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 10/05/2022] [Accepted: 11/23/2022] [Indexed: 11/27/2022] Open
Abstract
Neuronal cultures are a prominent experimental tool to understand complex functional organization in neuronal assemblies. However, neurons grown on flat surfaces exhibit a strongly coherent bursting behavior with limited functionality. To approach the functional richness of naturally formed neuronal circuits, here we studied neuronal networks grown on polydimethylsiloxane (PDMS) topographical patterns shaped as either parallel tracks or square valleys. We followed the evolution of spontaneous activity in these cultures along 20 days in vitro using fluorescence calcium imaging. The networks were characterized by rich spatiotemporal activity patterns that comprised from small regions of the culture to its whole extent. Effective connectivity analysis revealed the emergence of spatially compact functional modules that were associated with both the underpinned topographical features and predominant spatiotemporal activity fronts. Our results show the capacity of spatial constraints to mold activity and functional organization, bringing new opportunities to comprehend the structure-function relationship in living neuronal circuits.
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Affiliation(s)
- Marc Montalà-Flaquer
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, E-08028 Barcelona, Spain,Universitat de Barcelona Institute of Complex Systems (UBICS), E-08028 Barcelona, Spain
| | - Clara F. López-León
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, E-08028 Barcelona, Spain,Universitat de Barcelona Institute of Complex Systems (UBICS), E-08028 Barcelona, Spain
| | - Daniel Tornero
- Laboratory of Neural Stem Cells and Brain Damage, Institute of Neurosciences, University of Barcelona, E-08036 Barcelona, Spain
| | - Akke Mats Houben
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, E-08028 Barcelona, Spain,Universitat de Barcelona Institute of Complex Systems (UBICS), E-08028 Barcelona, Spain
| | - Tanguy Fardet
- Laboratoire Matière et Systèmes Complexes, Université de Paris, UMR 7057 CNRS, Paris, France,University of Tübingen, Tübingen, Germany,Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Pascal Monceau
- Laboratoire Matière et Systèmes Complexes, Université de Paris, UMR 7057 CNRS, Paris, France
| | - Samuel Bottani
- Laboratoire Matière et Systèmes Complexes, Université de Paris, UMR 7057 CNRS, Paris, France
| | - Jordi Soriano
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, E-08028 Barcelona, Spain,Universitat de Barcelona Institute of Complex Systems (UBICS), E-08028 Barcelona, Spain,Corresponding author
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Rapisardi G, Kryven I, Arenas A. Percolation in networks with local homeostatic plasticity. Nat Commun 2022; 13:122. [PMID: 35013243 PMCID: PMC8748765 DOI: 10.1038/s41467-021-27736-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 11/30/2021] [Indexed: 12/03/2022] Open
Abstract
Percolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportation systems. Some biological systems, such as networks of neural cells, actively respond to percolation-like damage, which enables these structures to maintain their function after degradation and aging. Here we study percolation in networks that actively respond to link damage by adopting a mechanism resembling synaptic scaling in neurons. We explain critical transitions in such active networks and show that these structures are more resilient to damage as they are able to maintain a stronger connectedness and ability to spread information. Moreover, we uncover the role of local rescaling strategies in biological networks and indicate a possibility of designing smart infrastructures with improved robustness to perturbations.
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Affiliation(s)
- Giacomo Rapisardi
- Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, E-43007, Tarragona, Spain
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Ivan Kryven
- Mathematical Institute, Utrecht University, Budapestlaan 6, 3508 TA, Utrecht, The Netherlands
- Centre for Complex Systems Studies, 3584 CE, Utrecht, The Netherlands
| | - Alex Arenas
- Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, E-43007, Tarragona, Spain.
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